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Prediction of meditation experience using fMRI functional connectivity and multivariate pattern analysis

机译:使用FMRI功能连通性和多变量模式分析预测冥想体验

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Mindfulness meditation is a complex psychological process that involves emotional, attentional and awareness practices. In this work, we predict the years of meditation experience of Buddhist monks using Multivariate Pattern Regression and functional connectivity analysis. 12 Buddhist monks underwent a meditation session according to two meditation styles while BOLD fMRI at 1.5 T was recorded. Functional connectivity matrices were calculated between functionally subdivided ROIs. Correlations were used as features for a Support Vector Regression with target the monks' experience. Regression weights highlighted prominent connections and differentiated meditation styles.
机译:介意冥想是一种复杂的心理过程,涉及情感,注意力和意识实践。 在这项工作中,我们预测了使用多元模式回归和功能连接分析的佛教僧侣冥想体验。 12佛教僧侣根据两种冥想风格接受冥想会议,而录制1.5 T的大胆FMRI。 在功能细分的ROI之间计算功能连接矩阵。 相关性被用作支持僧侣体验的支持向量回归的特征。 回归权重突出显示突出的连接和差异化的冥想风格。

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